Noise Removal of ECG Signal Using Recursive LeastSquare Algorithms
This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). S...
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Al-Khwarizmi College of Engineering – University of Baghdad
2011
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/59caa7a3bea547a2b6dc8daf6438c8ee |
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| Sumario: | This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did. |
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